Editing Test:SRCCL/Chapter-1 (section)

==== Interactions between land and climate system components and models in scenario analysis. The blue text describes selected model inputs and outputs. ====

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Interactions between land and climate system components and models in scenario analysis. The blue text describes selected model inputs and outputs.

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Normative scenarios: visions and pathways analysis

Normative scenarios reflect a desired or target-seeking future. Pathways analysis is important in moving beyond the ‘what if?’ perspective of exploratory scenarios to evaluate how normative futures might be achieved in practice, recognising that multiple pathways may achieve the same future vision. Pathways analysis focuses on consumption and behavioural changes through transitions and transformative solutions (IPBES 2018a <sup>[[#fn:r501|501]]</sup> ). Pathways analysis is highly relevant in support of policy, since it outlines sets of time-dependent actions and decisions to achieve future targets, especially with respect to sustainable development goals, as well as highlighting trade-offs and co-benefits (IPBES 2018a <sup>[[#fn:r502|502]]</sup> ). Multiple, alternative pathways have been shown to exist that mitigate trade-offs whilst achieving the priorities for future sustainable development outlined by governments and societal actors. Of these alternatives, the most promising focus on long-term societal transformations through education, awareness raising, knowledge sharing and participatory decision-making (IPBES 2018a <sup>[[#fn:r503|503]]</sup> ).

What are the limitations of land-use scenarios?

Applying a common scenario framework (e.g., RCPs/SSPs) supports the comparison and integration of climate- and land-system scenarios, but a ‘climate-centric’ perspective can limit the capacity of these scenarios to account for a wider range of land-relevant drivers (Rosa et al. 2017 <sup>[[#fn:r504|504]]</sup> ). For example, in climate mitigation scenarios it is important to assess the impact of mitigation actions on the broader environment such as biodiversity, ecosystem functioning, air quality, food security, desertification/degradation and water cycles (Rosa et al. 2017 <sup>[[#fn:r505|505]]</sup> ). This implies the need for a more encompassing and flexible approach to creating scenarios that considers other environmental aspects, not only as a part of impact assessment, but also during the process of creating the scenarios themselves.

A limited number of models can quantify global scale, land-use change scenarios, and there is large variance in the outcomes of these models (Alexander et al. 2016a <sup>[[#fn:r506|506]]</sup> ; Prestele et al. 2016 <sup>[[#fn:r507|507]]</sup> ). In some cases, there is greater variability between the models themselves than between the scenarios that they are quantifying, and these differences vary geographically (Prestele et al. 2016 <sup>[[#fn:r508|508]]</sup> ). These differences arise from variations in baseline datasets, thematic classes and modelling paradigms (Alexander et al. 2016a <sup>[[#fn:r509|509]]</sup> ; Popp et al. 2016 <sup>[[#fn:r510|510]]</sup> ; Prestele et al. 2016 <sup>[[#fn:r511|511]]</sup> ). Model evaluation is critical in establishing confidence in the outcomes of modelled futures (Ahlstrom et al. 2012 <sup>[[#fn:r512|512]]</sup> ; Kelley et al. 2013 <sup>[[#fn:r513|513]]</sup> ). Some, but not all, land-use models are evaluated against observational data and model evaluation is rarely reported. Hence, there is a need for more transparency in land-use modelling, especially in evaluation and testing, as well as making model code available with complete sets of scenario outputs (e.g., Dietrich et al. 2018 <sup>[[#fn:r514|514]]</sup> ).

There is a small, but growing literature on quantitative pathways to achieve normative visions and their associated trade-offs (IPBES 2018a <sup>[[#fn:r515|515]]</sup> ). Whilst the visions themselves may be clearly articulated, the societal choices, behaviours and transitions needed to attain them, are not. Better accounting for human behaviour and decision-making processes in global scale land-use models would improve the capacity to quantify pathways to sustainable futures (Rounsevell et al. 2014 <sup>[[#fn:r516|516]]</sup> ; Arneth et al. 2014 <sup>[[#fn:r517|517]]</sup> ; Calvin and Bond-Lamberty 2018 <sup>[[#fn:r518|518]]</sup> ). It is, however, difficult to understand and represent human behaviour and social interaction processes at global scales. Decision-making in global models is commonly represented through economic processes (Arneth et al. 2014 <sup>[[#fn:r519|519]]</sup> ). Other important human processes for land systems including equity, fairness, land tenure and the role of institutions and governance, receive less attention, and this limits the use of global models to quantify transformative pathways, adaptation and mitigation (Arneth et al. 2014 <sup>[[#fn:r520|520]]</sup> ; Rounsevell et al. 2014 <sup>[[#fn:r521|521]]</sup> ; Wang et al. 2016 <sup>[[#fn:r|]]</sup> 522). No model exists at present to represent complex human behaviours at the global scale, although the need has been highlighted (Rounsevell et al. 2014 <sup>[[#fn:r523|523]]</sup> ; Arneth et al. 2014 <sup>[[#fn:r524|524]]</sup> ; Robinson et al. 2017 <sup>[[#fn:r525|525]]</sup> ; Brown et al. 2017 <sup>[[#fn:r526|526]]</sup> ; Calvin and Bond-Lamberty 2018 <sup>[[#fn:r527|527]]</sup> ).

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